Recognizing Human-Object Interactions Using Sparse Subspace Clustering
نویسندگان
چکیده
This is a difficult because: 1. Object appearance varies 2. Way of interacting with object vary among people 3. Both object and body parts of the interest might be occluded Contributions By using motion information alone, we propose an unsupervised framework for clustering and classifying videos of people interacting with objects. The method is based on [2]. We show that: 1. human-object interactions can be seen as trajectories lying on a union of low-dimensional subspaces 2. Sparse subspace clustering is able to recover subspaces Method
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تاریخ انتشار 2013